About the service
I create industrial solutions based on natural language processing and transform raw, unstructured text into clean structured data that can be queried and used to make decisions. Over the years, I have deployed classifiers, entity extractors, and sentiment engines for support services, legal departments, marketplaces, and media monitoring systems, and I understand the difference between a demo that looks good on a slide and a pipeline that withstands real request traffic. When you bring me an array of tickets, contracts, reviews, or chat logs, I start by asking what problem this text should solve, because this framing determines everything that follows: the label set, metrics, and acceptable error budget.
My work covers the full spectrum of tasks. I train and tune text classification for routing, moderation, and intent detection; extract named entities—people, organizations, amounts, dates, and your industry-specific terms; compute sentiment and emotions; prepare abstract and extractive summaries; tune topic modeling and semantic search so your team searches for meaning, not word matches. Where an off-the-shelf model gets you most of the way, I fine-tune it on your labeled data, calibrate thresholds, and deliver a model that speaks your vocabulary, not a generalized one.
You get more than a notebook with code. I hand over a documented pipeline, an evaluation report with honest accuracy and recall figures for each class, a ready-made API or batch task for integration, and clear notes on model weaknesses so there are no surprises in production. Maintainability matters to me: reproducible training, data versioning, and monitoring hooks so drift is caught early. Tell me about languages, volumes, and target accuracy—and I'll propose a realistic plan.
— Text classification, routing, and moderation
— Named entity extraction and custom taxonomies
— Sentiment, summarization, topics, and semantic search
— Fine-tuning language models on your data
My work covers the full spectrum of tasks. I train and tune text classification for routing, moderation, and intent detection; extract named entities—people, organizations, amounts, dates, and your industry-specific terms; compute sentiment and emotions; prepare abstract and extractive summaries; tune topic modeling and semantic search so your team searches for meaning, not word matches. Where an off-the-shelf model gets you most of the way, I fine-tune it on your labeled data, calibrate thresholds, and deliver a model that speaks your vocabulary, not a generalized one.
You get more than a notebook with code. I hand over a documented pipeline, an evaluation report with honest accuracy and recall figures for each class, a ready-made API or batch task for integration, and clear notes on model weaknesses so there are no surprises in production. Maintainability matters to me: reproducible training, data versioning, and monitoring hooks so drift is caught early. Tell me about languages, volumes, and target accuracy—and I'll propose a realistic plan.
— Text classification, routing, and moderation
— Named entity extraction and custom taxonomies
— Sentiment, summarization, topics, and semantic search
— Fine-tuning language models on your data
